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Neural Computing and Applications

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01.12.2013 | Original Article

A computer-aided diagnosis system for malignant melanomas

verfasst von: N. Razmjooy, B. Somayeh Mousavi, Fazlollah Soleymani, M. Hosseini Khotbesara

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2013

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Abstract

The aim of this study is to provide an efficient way to segment the malignant melanoma images. This method first eliminates extra hair and scales using edge detection; afterward, it deduces a color image into an intensity image and approximately segments the image by intensity thresholding. Some morphological operations are used to focus on an image area where a melanoma boundary potentially exists and then used to localize the boundary in that area. The distributions of texture and a new feature known as AIBQ features in the next step provide a good discrimination of skin lesions to feature extraction. Finally, we rely on quantitative image analysis to measure a series of candidate attributes hoped to contain enough information to differentiate malignant from benign melanomas. The selected features are applied to a support vector machine to classify the melanomas as malignant or benign. By our approach, we obtained 95 % correct classification of malignant or benign melanoma on real melanoma images.

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Titel: A computer-aided diagnosis system for malignant melanomas
verfasst von: N. Razmjooy
B. Somayeh Mousavi
Fazlollah Soleymani
M. Hosseini Khotbesara
Publikationsdatum: 01.12.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7-8/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-1149-1

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